Microsoft and Red Hat are delivering on choice by announcing
the availability of Microsoft SQL Server 2017 on Red Hat Enterprise Linux, the
world’s leading enterprise Linux platform. As Microsoft’s reference Linux
platform for SQL Server, Red Hat Enterprise Linux extends the enterprise
database and analytics capabilities of SQL Server by delivering it on the
industry-leading platform for performance, security features, stability,
reliability, and manageability.

Customers will be able to bring the performance and security
features of SQL Server to Linux workloads. SQL Server 2017 on Red Hat
Enterprise Linux delivers mission-critical OLTP database capabilities and
enterprise data warehousing with in-memory technology across workloads. SQL
Server 2017 embraces developers by delivering choice in language and platform,
with container support that seamlessly facilitates DevOps scenarios. The new
release of SQL Server delivers all of this, built-in. And, it runs wherever you
want, whether in your datacenter, in Azure virtual machines, or in containers
running on Red Hat OpenShift

Also starting October 2nd until June 30th, 2018, Microsoft
is launching a SQL Server on Red Hat Enterprise Linux offer to help with
upgrades and migrations. This offer provides up to 30% off SQL Server 2017
through an annual subscription. When customers purchase a new Red Hat
Enterprise Linux subscription to support their SQL Server, they will be
eligible for another 30% off their Red Hat Enterprise Linux subscription price.

In addition to discounts on SQL Server and Red Hat
Enterprise Linux, all of this is backed by integrated support from Microsoft
and Red Hat.

There are a number of new features for SQL Server that Microsoft
think make this the best release ever. Here are just a few:

Container support
seamlessly facilitates your development and DevOps scenarios by enabling you to
quickly spin up SQL Server containers and get rid of them when you are
finished. SQL Server supports Docker Enterprise Edition, Kubernetes and
OpenShift container platforms.

AI with R and Python
analytics enables you to build intelligent apps using scalable,
GPU-accelerated, parallelized R and now Python analytics running in the
database.

Graph data analysis
will enable customers to use graph data storage and query language extensions
for graph-native query syntax to discover new kinds of relationships in highly
interconnected data.

Adaptive Query Processing
is a new family of features in SQL Server that bring intelligence to database
performance. For example, Adaptive Memory Grants in SQL Server track and learn
from how much memory is used by a given query to right-size memory grants.